Anne Beeson Royalty
Department of Economics
Cavanaugh Hall (CA) 509D
425 University Boulevard
Indianapolis, IN 46202
Information about this author at RePEc
NBER Working Papers and Publications
|June 2019||The Effects of Multispecialty Group Practice on Health Care Spending and Use|
with , : w25915
U.S. physicians are increasingly joining multispecialty group practices. In this paper, we analyze how a primary care physician’s practice type – single (SSP) versus multispecialty practice (MSP) – affects health care spending and use. Focusing on Medicare beneficiaries who change their primary care physician due to a geographic move, we compare changes in practice patterns before and after the move between patients who switch practice types and those who do not. We use instrumental variables to address potential selection by patients into practice types after the move. We find that changing from a single to a multi-specialty primary care group practice decreases annual Medicare-financed per capita expenditures by about $1,600 - a 28% reduction. The effect is driven primarily by change...
|October 2016||Measuring Physician Practice Competition Using Medicare Data|
in Measuring and Modeling Health Care Costs, Ana Aizcorbe, Colin Baker, Ernst R. Berndt, and David M. Cutler, editors
Questions about the market structure of physician practices have become prominent in contemporary health policy discussions. Market forces recently appear to favor the growth of larger multi-specialty groups. Larger practices could lead to improvements in health care quality and outcomes by improving coordination, but they may be more difficult to effectively manage and, if inefficient, could drive higher costs of care. Larger practices may also increase concentration in health care markets. While concentration has been well studied in the case of hospitals, there is less evidence about impacts of structural changes in physician markets. A primary reason is a lack of regularly collected, broadly based data on practice market structure. In this paper, we explore the creation of physician pr...
|July 2011||Gauging the Generosity of Employer-Sponsored Insurance: Differences Between Households With and Without a Chronic Condition|
with , : w17232
We develop an empirical method to assess the generosity of employer-sponsored insurance across groups within the U.S. population. A key feature of this method is its simplicity - it only requires data on out-of-pocket (OOP) health care spending and total health care spending and does not require detailed knowledge of health insurance benefit design. We apply our method to assess whether households with a chronically ill member have more or less generous insurance relative to households with no chronically ill members. We find that the chronically ill have less generous insurance coverage than the non-chronically ill. Additional analyses suggest that the reason for this less generous coverage is not that households with a chronically ill member are in different, less generous plans, on av...
|October 2009||Moral Hazard Matters: Measuring Relative Rates of Underinsurance Using Threshold Measures|
with , : w15410
This paper illustrates the impact of moral hazard for estimating relative rates of underinsurance and to present an adjustment method to correct for this source of bias. Individuals or households are often classified as underinsured if out-of-pocket spending on medical care relative to income exceeds some threshold. We show that, without adjustment, this common threshold measure of underinsurance will underestimate the number with low levels of insurance coverage due to moral hazard. We propose an adjustment method and apply it to the specific case of estimating the difference in rates of underinsurance among small- versus large-firm workers with full-year, employer-sponsored insurance. Using data from the 2005 Medical Expenditure Panel Survey, we find that after applying the adjustment,...
Published: Abraham, Jean Marie, Thomas DeLeire, and Anne Bees on Royalty . (2010). “Moral Hazard Matters: Measuring Relative Rates of Underinsurance Using Threshold Measures” Health Services Research 45(3): 806 - 824.